【2021年】NVIDIA Jetsonの JetPack 4.5.1環境で PyTorch 1.7.1をビルドする方法
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【2021年】NVIDIA Jetsonの JetPack 4.5.1環境で PyTorch 1.7.1をビルドする方法| Xavier NX | Nano | |
| 性能比 | 6～30倍 | 1 |
| AI性能比 | 21 TOPs | 472 GFLOPs |
| メモリ | 8GB | 4GB |
| M.2 SSD | 対応 | 非対応 |
| 電源 | 付属 | 別売り |
| ファン | 内蔵 | 別売り |
| SDカード | 別売り | 別売り |
| ケース | 別売り | 別売り |
| 消費電力 | 10W / 15W | 5W / 10W |
 NVIDIA Jetson Xavier NX Developer Kit 開発キット クラウドネイティブ AIコンピュータ ディープラーニング ASIN: B088TTD1QT ※ 低価格のハイエンドモデル |
 NVIDIA Jetson Nano Development Kit B01 開発キット AI コンピュータ 人工知能 エッジコンピューティング ASIN: B085NQTKS9 ※ 入門用の低価格 4GB版 |
 GeeekPi Jetson Nanoケース（Jetson Nano B01およびA02バージョンをサポート）NVIDIA Jetson Nano開発者キットに適したファン付きJetson NanoケースSmall AI Powerful Computer ASIN: B085PZ4F3X |
 SanDisk ( サンディスク ) 128GB microSD Extreme PRO microSDXC A2 SDSQXCY-128G-GN6MA ［ 海外パッケージ品 ］ ASIN: B07G3H5RBT ※ 高速、大容量 SDカード |
# https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-7-0-now-available/72048 # Build wheel for Python 3.6 (to pytorch/dist) sudo apt-get install -y python3-pip cmake libopenblas-dev export USE_NCCL=0 # skip setting this if you want to enable OpenMPI backend export USE_DISTRIBUTED=0 export USE_QNNPACK=0 export USE_PYTORCH_QNNPACK=0 export TORCH_CUDA_ARCH_LIST="5.3;6.2;7.2" # without the leading 'v', e.g. 1.3.0 for PyTorch v1.3.0 export PYTORCH_BUILD_VERSION=1.7.1 export PYTORCH_BUILD_NUMBER=1
cd git clone --recursive --branch v$PYTORCH_BUILD_VERSION http://github.com/pytorch/pytorch --depth 1 cd pytorch # Apply Patch PyTorch issue #8103 # too many CUDA resources requested for launch error # https://github.com/pytorch/pytorch/issues/8103#issuecomment-514802040 # https://gist.github.com/dusty-nv/ce51796085178e1f38e3c6a1663a93a1#file-pytorch-1-7-jetpack-4-4-1-patch # // See https://github.com/pytorch/pytorch/issues/47098 # // patch for gcc 7 bug returns incorrect result on aarch64 if compiled by gcc-7.5.0 sed -i 's/#if defined(__aarch64__)/#if defined(__aarch64__)\n#if defined(__clang__) || (__GNUC__ > 8 || (__GNUC__ == 8 \&\& __GNUC_MINOR__ > 3))/' aten/src/ATen/cpu/vec256/vec256_float_neon.h sed -i 's/}}}/#endif\n}}}/' aten/src/ATen/cpu/vec256/vec256_float_neon.h # // patch for "too many resources requested for launch" sed -i 's/device_prop, device_index));$/device_prop, device_index));\n device_prop.maxThreadsPerBlock = device_prop.maxThreadsPerBlock \/ 2;/' aten/src/ATen/cuda/CUDAContext.cpp grep maxThreadsPerBlock aten/src/ATen/cuda/CUDAContext.cpp # // patch for "too many resources requested for launch" sed -i 's/int CUDA_NUM_THREADS = .*;/int CUDA_NUM_THREADS = 512;/' aten/src/ATen/cuda/detail/KernelUtils.h grep CUDA_NUM_THREADS aten/src/ATen/cuda/detail/KernelUtils.h # // patch for "too many resources requested for launch" sed -i 's/int CUDA_NUM_THREADS = .*;/int CUDA_NUM_THREADS = 512;/' aten/src/THCUNN/common.h grep CUDA_NUM_THREADS aten/src/THCUNN/common.h
sudo pip3 install -r requirements.txt sudo pip3 install scikit-build # Successfully installed distro-1.5.0 packaging-20.9 pyparsing-2.4.7 scikit-build-0.11.1 sudo pip3 install ninja # Successfully installed ninja-1.10.0.post2 free -h # Jetson Xavier NX # total used free shared buff/cache available # Mem: 7.6G 305M 5.1G 20M 2.2G 7.1G # Swap: 3.8G 0B 3.8G # Jetson Nano # total used free shared buff/cache available # Mem: 3.9G 225M 1.5G 18M 2.1G 3.5G # Swap: 1.9G 0B 1.9G # if Jetson Nano Need export MAX_JOBS=3 to Reduce Memory usage export MAX_JOBS=3 time python3 setup.py bdist_wheel # Jetson Xavier NX # real 355m36.122s # user 1941m55.096s # sys 78m0.800s # Jetson Nano # real 698m59.398s # user 1927m0.192s # sys 80m49.916s find ./ -name "*.whl" # ./dist/torch-1.7.1-cp36-cp36m-linux_aarch64.whl ls -l ./dist/torch-1.7.1-cp36-cp36m-linux_aarch64.whl # -rw-rw-r-- 1 jetson jetson 249073141 Mar 1 22:24 ./dist/torch-1.7.1-cp36-cp36m-linux_aarch64.whl
# Install PyTorch 1.7.1 from wheel
sudo apt-get install -y libopenblas-base libopenmpi-dev
# RuntimeError: Python version >= 3.7 required
sudo pip3 install Cython==0.29.22
sudo pip3 install numpy==1.19.5
# The headers or library files could not be found for jpeg,
# a required dependency when compiling Pillow from source.
#
# Please see the install instructions at:
# https://pillow.readthedocs.io/en/latest/installation.html
# Prerequisites for Ubuntu 16.04 LTS - 20.04 LTS are installed with
# https://pillow.readthedocs.io/en/latest/installation.html
sudo apt-get install -y libtiff5-dev libjpeg8-dev libopenjp2-7-dev zlib1g-dev \
libfreetype6-dev liblcms2-dev libwebp-dev tcl8.6-dev tk8.6-dev python3-tk \
libharfbuzz-dev libfribidi-dev libxcb1-dev
sudo pip3 install Pillow==8.1.0
sudo pip3 install matplotlib==3.3.3
# sudo pip3 install --upgrade --force-reinstall ./dist/torch-1.7.1-cp36-cp36m-linux_aarch64.whl
sudo pip3 install ./dist/torch-1.7.1-cp36-cp36m-linux_aarch64.whl
# Successfully installed torch-1.7.1
pip3 list --format=legacy | grep torch
# torch (1.7.1)
cd
python3 -c "import torch; print(torch.__version__); print(torch.cuda.is_available()); print(torch.cuda.get_device_name())"
# Jetson Xavier NX
# 1.7.1
# True
# Xavier
# Jetson Nano
# 1.7.1
# True
# NVIDIA Tegra X1
# torchvision v0.8.2 sudo apt-get install -y libavcodec-dev sudo apt-get install -y libavformat-dev sudo apt-get install -y libswscale-dev cd git clone --recursive --branch v0.8.2 https://github.com/pytorch/vision --depth 1 cd vision time sudo python3 setup.py install # Using /usr/local/lib/python3.6/dist-packages # Finished processing dependencies for torchvision==0.8.0a0+2f40a48 # Jetson Xavier NX # real 4m18.352s # user 19m39.352s # sys 1m44.984s cd python3 -c "import torchvision; print(torchvision.__version__);" # 0.8.0a0+2f40a48 (torchvision v0.8.2) pip3 list --format=legacy | grep torch # torch (1.7.1) # torchvision (0.8.0a0+2f40a48)
python3 -c "import torch; print(torch.__version__); print(torch.cuda.is_available()); print(torch.cuda.get_device_name())" python3 -c "import torchvision; print(torchvision.__version__);"
